RTX 5090 vs RTX Pro 6000 Blackwell - GPU Benchmark Comparison

Direct performance comparison between the RTX 5090 and RTX Pro 6000 Blackwell across 27 standardized AI benchmarks collected from our production fleet. Testing shows the RTX 5090 winning 13 out of 27 benchmarks (48% win rate), while the RTX Pro 6000 Blackwell wins 14 tests. All benchmark results are automatically gathered from active rental servers, providing real-world performance data.

vLLM High-Throughput Inference: RTX 5090 62% slower

For production API servers and multi-agent AI systems running multiple concurrent requests, the RTX 5090 is 62% slower than the RTX Pro 6000 Blackwell (median across 3 benchmarks). For Qwen/Qwen3-4B, the RTX 5090 reaches 954 tokens/s while RTX Pro 6000 Blackwell achieves 2481 tokens/s (62% slower). The RTX 5090 wins none out of 3 high-throughput tests, making the RTX Pro 6000 Blackwell better suited for production API workloads.

Ollama Single-User Inference: RTX 5090 14% faster

For personal AI assistants and local development with one request at a time, the RTX 5090 is 14% faster than the RTX Pro 6000 Blackwell (median across 8 benchmarks). Running llama3.1:8b, the RTX 5090 generates 264 tokens/s vs RTX Pro 6000 Blackwell's 226 tokens/s (17% faster). The RTX 5090 wins 8 out of 8 single-user tests, making it ideal for personal coding assistants and prototyping.

Image Generation: RTX 5090 14% slower

For Stable Diffusion, SDXL, and Flux workloads, the RTX 5090 is 14% slower than the RTX Pro 6000 Blackwell (median across 12 benchmarks). Testing sd3.5-large, the RTX 5090 completes at 12 s/image while RTX Pro 6000 Blackwell achieves 8.3 s/image (28% slower). The RTX 5090 wins 4 out of 12 image generation tests, making the RTX Pro 6000 Blackwell the better choice for Stable Diffusion workloads.

Vision AI: RTX 5090 23% lower throughput

For high-concurrency vision workloads (16-64 parallel requests), the RTX 5090 delivers 23% lower throughput than the RTX Pro 6000 Blackwell (median across 2 benchmarks). Testing llava-1.5-7b, the RTX 5090 processes 336 images/min while RTX Pro 6000 Blackwell achieves 440 images/min (24% slower). The RTX 5090 wins none out of 2 vision tests, making the RTX Pro 6000 Blackwell the better choice for high-throughput vision AI workloads.

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About These Benchmarks of RTX 5090 vs RTX Pro 6000 Blackwell

Our benchmarks are collected automatically from servers having GPUs of type RTX 5090 and RTX Pro 6000 Blackwell in our fleet. Unlike synthetic lab tests, these results come from real production servers handling actual AI workloads - giving you transparent, real-world performance data.

LLM Inference Benchmarks

We test both vLLM (High-Throughput) and Ollama (Single-User) frameworks. vLLM benchmarks show how RTX 5090 and RTX Pro 6000 Blackwell perform with 16-64 concurrent requests - perfect for production chatbots, multi-agent AI systems, and API servers. Ollama benchmarks measure single-request speed for personal AI assistants and local development. Models tested include Llama 3.1, Qwen3, DeepSeek-R1, and more.

Image Generation Benchmarks

Image generation benchmarks cover Flux, SDXL, and SD3.5 architectures. That's critical for AI art generation, design prototyping, and creative applications. Focus on single prompt generation speed to understand how RTX 5090 and RTX Pro 6000 Blackwell handle your image workloads.

Vision AI Benchmarks

Vision benchmarks test multimodal and document processing with high concurrent load (16-64 parallel requests) using real-world test data. LLaVA 1.5 7B (7B parameter Vision-Language Model) analyzes a photograph of an elderly woman in a flower field with a golden retriever, testing scene understanding and visual reasoning at batch size 32 to report images per minute. TrOCR-base (334M parameter OCR model) processes 2,750 pages of Shakespeare's Hamlet scanned from historical books with period typography at batch size 16, measuring pages per minute for document digitization. See how RTX 5090 and RTX Pro 6000 Blackwell handle production-scale visual AI workloads - critical for content moderation, document processing, and automated image analysis.

System Performance

We also include CPU compute power (affecting tokenization and preprocessing) and NVMe storage speeds (critical for loading large models and datasets) - the complete picture for your AI workloads.

TAIFlops Score

The TAIFlops (Trooper AI FLOPS) score shown in the first row combines all AI benchmark results into a single number. Using the RTX 3090 as baseline (100 TAIFlops), this score instantly tells you how RTX 5090 and RTX Pro 6000 Blackwell compare overall for AI workloads. Learn more about TAIFlops β†’

Note: Results may vary based on system load and configuration. These benchmarks represent median values from multiple test runs.

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